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Supervised Learning with Complex-valued Neural Networks
Recent advancements in the field of telecommunications, medical imaging and signal processing deal with signals that are inherently time varying, nonlinear and complex-valued. The time varying, nonlinear characteristics of these signals can be effectively analyzed using artificial neural networks. ...
| Autores principales: | , , |
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| Lenguaje: | eng |
| Publicado: |
Springer
2013
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| Materias: | |
| Acceso en línea: | https://dx.doi.org/10.1007/978-3-642-29491-4 http://cds.cern.ch/record/1500278 |